SoroushVahidi/scidocs huggingface dataset:
S-Sensors: Integrating physical world inputs with social networks using wireless sensor networks
(2009)

Real-world monitoring and surveillance applications are rapidly increasing with the growth in the demand for awareness of the environment and surrounding. Sensor-to-web integration models are envisaged to improve the utilisation of sensory infrastructures and data via advanced coordination and collaboration of sensor nodes and web applications. This paper proposes to employ micro-blogging to publish and share sensory data and resources. S-Sensors provides a framework to globally share locally measured sensory readings. Short messages depicting the status of the environment are used to convey sensory data of the physical world. Moreover, data accessibility and resource manageability are facilitated by using social networks paradigms to form communities of sensor networks.
Development of ambient environmental monitoring system through wireless sensor network (WSN) using NodeMCU and “WSN monitoring”
(2017)

In this paper we have developed a system for web based environment monitoring using the WSN Technology. WSN sensor nodes transmit data to the cloud-based database via Web API request. Measured data can be monitored by the user anywhere from internet by using the Web Application which one is also compatible for mobile phones. If the data measured by sensor node exceeds the configured value range in Web Application, Web Application sends a warning e-mail to users for improving environmental conditions.
Multicenter randomized clinical trial evaluating the effectiveness of the Lokomat in subacute stroke.
(2009)

OBJECTIVE
To compare the efficacy of robotic-assisted gait training with the Lokomat to conventional gait training in individuals with subacute stroke.


METHODS
A total of 63 participants<6 months poststroke with an initial walking speed between 0.1 to 0.6 m/s completed the multicenter, randomized clinical trial. All participants received twenty-four 1-hour sessions of either Lokomat or conventional gait training. Outcome measures were evaluated prior to training, after 12 and 24 sessions, and at a 3-month follow-up exam. Self-selected overground walking speed and distance walked in 6 minutes were the primary outcome measures, whereas secondary outcome measures included balance, mobility and function, cadence and symmetry, level of disability, and quality of life measures.


RESULTS
Participants who received conventional gait training experienced significantly greater gains in walking speed (P=.002) and distance (P=.03) than those trained on the Lokomat. These differences were maintained at the 3-month follow-up evaluation. Secondary measures were not different between the 2 groups, although a 2-fold greater improvement in cadence was observed in the conventional versus Lokomat group.


CONCLUSIONS
For subacute stroke participants with moderate to severe gait impairments, the diversity of conventional gait training interventions appears to be more effective than robotic-assisted gait training for facilitating returns in walking ability.
Advances in Neuropsychoanalysis , Attachment Theory , and Trauma Research : Implications for Self Psychology
(2002)

In 1971, Heinz Kohut, trained in neurology and then psychoanalysis, published The Analysis of the Self, a detailed exposition of the central role of the self in human existence. This classic volume of both twentieth century psychoanalysis and psychology was more than a collection of various clinical observations—rather it represented an overarching integrated theory of the development, structuralization, psychopathogenesis, and psychotherapy of disorders of the self. Although some of these ideas were elaborations of previous psychoanalytic principles, a large number of his concepts, including an emphasis on self rather than ego, signified an innovative departure from mainstream psychoanalysis and yet a truly creative addition to Freud’s theory.
Linearization Through Dithering: A 50 MHz Bandwidth, 10-b ENOB, 8.2 mW VCO-Based ADC
(2015)

Non-linear voltage-to-frequency characteristic of a voltage-controlled oscillator (VCO) severely curtails the dynamic range of analog-to-digital converters (ADCs) built with VCOs. Typical approaches to enhance the dynamic range include embedding the VCO-based ADC in a ΔΣ loop or to post-process the digital data for calibration, both of which impose significant power constraints. In contrast, in this work the VCO-based ADC is linearized through a filtered dithering technique, wherein the VCO-based ADC is used as a fine stage that processes the residue from a coarse stage in a 0-1 MASH structure. The proposed filtered dithering technique conditions the signal to the VCO input to appear as white noise thereby eliminating spurious signal content arising out of the VCO nonlinearity. The work resorts to multiple other signal processing techniques to build a high-resolution, wideband prototype, in 65 nm complementary metal-oxide semiconductor (CMOS), that achieves 10 effective number of bits (ENOB) in digitizing signals with 50 MHz bandwidth consuming 8.2 mW at a figure of merit (FoM) of 90 fJ/conv.step.
Image compression with auto-encoder algorithm using deep neural network (DNN)
(2016)

An image compression is necessary for the image processing applications such as data storing, image classification, image recognition etc. Then, several research articles have been proposed to reserve for these topics. However, the image compression with auto encoder has been found for a small number of the improvements. Therefore, this paper presents a detailed study to demonstrate the image compression algorithm using the deep neural network (DNN). The proposed algorithm consists of 1) compressing image with auto encoder, and 2) decoding image. The proposed compressing image with auto encoder algorithm uses non-recurrent three-layer neural networks (NRTNNs) which use an extended Kalman filter (EKF) to update the weights of the networks. To evaluate the proposed algorithm performances, the Matlab program is used for implementations of the overall testing algorithm. From our simulation results, it shows that the proposed image compression algorithm is able to reduce the image dimensionality and is able to recall the compressed image with low loss.
Distribution expansion planning considering reliability and security of energy using modified PSO ( Particle Swarm Optimization ) algorithm
(2017)

Distribution feeders and substations need to provide additional capacity to serve the growing electrical demand of customers without compromising the reliability of the electrical networks. Also, more control devices, such as DG (Distributed Generation) units are being integrated into distribution feeders. Distribution networks were not planned to host these intermittent generation units before construction of the systems. Therefore, additional distribution facilities are needed to be planned and prepared for the future growth of the electrical demand as well as the increase of network hosting capacity by DG units. This paper presents a multiobjective optimization algorithm for the MDEP (Multi-Stage Distribution Expansion Planning) in the presence of DGs using nonlinear formulations. The objective functions of the MDEP consist of minimization of costs, END (Energy-Not-Distributed), active power losses and voltage stability index based on SCC (Short Circuit Capacity). A MPSO (modified Particle Swarm Optimization) algorithm is developed and used for this multiobjective MDEP optimization. In the proposed MPSO algorithm, a new mutation method is implemented to improve the global searching ability and restrain the premature convergence to local minima. The effectiveness of the proposed method is tested on a typical 33-bus test system and results are presented.
Word similarity computation based on HowNet
(2015)

Word similarity computation has important applications in many areas, such as natural language processing, intelligence information retrieval, document clustering, automatic answering, word sense disambiguation, machine translation etc. This article makes an intensive study of word similarity computation based on HowNet and the word similarity is computed in three steps: (1) computes sememes similarity, (2) computes concepts similarity using the weight sum method of sememes similarity, (3) takes the maximum similarity of concepts as words similarity. This article mainly introduces numbering the sememes and presents a more accurate method of decomposing the concept description type. The experiment shows that the algorithm of word similarity presented in this article is simple and feasible, and the computed results are relatively consistent with awareness.
A Resource-Based Model For E-Commerce In Developing Countries
(2011)

Previous efforts in electronic commerce (e-commerce) research in developing countries shows that there is an acute lack of theoretical frameworks and empirical evidence to understand how developing country firms realize electronic commerce benefits amidst their national constraints. This paper sets out to develop a theoretically abstracted but contextually grounded model of how developing country firms can orient their resources and realize these benefits amidst their national constraints. A review of e-commerce and strategy management literature to develop a resource – based model for e-commerce benefits was undertaken. The process-based model provides an understanding of how to identify, integrate, and reconfigure resources to achieve electronic commerce benefits; provides propositions that serves as theoretical platforms for future empirically grounded research on electronic commerce in developing country contexts and brings organizations closer to identifying and categorizing the strategic value of resources and the role managerial capabilities and intangible resources play in sustaining e-commerce benefits. Finally, our findings provides organizations the strategic options to address resources which have lost their value or have become less valuable to their strategic orientation in e-commerce adoption thereby serving as a starting point of examining e-commerce in developing countries through the theoretical lens of information systems and strategic management.
Personalized Security Messaging : Nudges for Compliance with Browser Warnings
(2017)

Decades of psychology and decision-making research show that everyone makes decisions differently; yet security messaging is still one-size-fits-all. This suggests that we can improve outcomes by delivering information relevant to how each individual makes decisions. We tested this hypothesis by designing messaging customized for stable personality traits— specifically, the five dimensions of the General Decision-Making Style (GDMS) instrument. We applied this messaging to browser warnings, security messaging encountered by millions of web users on a regular basis. To test the efficacy of our nudges, we conducted experiments with 1,276 participants, who encountered a warning about broken HTTPS due to an invalid certificate under realistic circumstances. While the effects of some nudges correlated with certain traits in a statistically significant manner, we could not reject the null hypothesis—that the intervention did not affect the subjects’ behavior—for most of our nudges, especially after accounting for participants who did not pay close attention to the message. In this paper, we present the detailed results of our experiments, discuss potential reasons for why the outcome contradicts the decision-making research, and identify lessons for researchers based on our experience.
Coding of pleasant touch by unmyelinated afferents in humans
(2009)

Pleasant touch sensations may begin with neural coding in the periphery by specific afferents. We found that during soft brush stroking, low-threshold unmyelinated mechanoreceptors (C-tactile), but not myelinated afferents, responded most vigorously at intermediate brushing velocities (1−10 cm s−1), which were perceived by subjects as being the most pleasant. Our results indicate that C-tactile afferents constitute a privileged peripheral pathway for pleasant tactile stimulation that is likely to signal affiliative social body contact.
A Systematic Mapping Study on Software Reuse
(2010)

Context: Software reuse is considered as the key to a successful software development because of its potential to reduce the time to market, increase quality and reduce costs. This increase in demand made the software organizations to envision the use of software reusable assets which can also help in solving recurring problems. Till now, software reuse is confined to reuse of source code in the name of code scavenging. Now a day, software organizations are extending the concepts of software reuse to other life cycle objects as they realized that reuse of source code alone does not save money. The academia has put forward some assets as reusable and presented methods or approaches for reusing them. Also, for a successful software reuse the organizations should assess the value of reuse and keep track on their reuse programs. The other area which is vital for software reuse is the maintenance. Maintenance of reusable software has direct impact on the cost of the software. In this regard, academia has presented a number of techniques, methods, metrics and models for assessing the value of reuse and for maintaining the reusable software. Objectives: In our thesis, we investigate on the reusable assets and the methods/ approaches that are put forward by the academia for reusing those assets. Also a systematic mapping study is performed to investigate what techniques, methods, models and metrics for assessing the value of reuse and for maintaining the reused software are proposed and we also investigate their validation status as well. Methods: The databases like IEEE Xplore, ACM digital library, Inspec, Springer and Google scholar were used to search for the relevant studies for our systematic mapping study. We followed basic inclusion criteria along with detailed inclusion/exclusion criteria for selecting the appropriate article. Results: Through our systematic mapping study, we could summarize the list of 14 reusable assets along with the approaches/methods for reusing them. Taxonomy for assessing the value of reuse and taxonomy for maintaining the reusable software are presented. We also presented the methods/metrics/models/techniques for measuring reuse to assess its value and for maintaining the reusable software along with their validation status and areas in focus. Conclusion: We conclude that, there is a need for defining a standard set of reusable assets that are commonly accepted by the researchers in the field of software reuse. Most metrics/models/methods/approaches presented for assessing the value of reuse and for maintaining the reuse software are academically validated. Efforts have to be put on industrially validating them using the real data.
Design of Lightweight Authentication and Key Agreement Protocol for Vehicular Ad Hoc Networks
(2017)

Due to the widespread popularity in both academia and industry, vehicular ad hoc networks (VANETs) have been used in a wide range of applications starting from intelligent transportation to e-health and itinerary planning. This paper proposes a new decentralized lightweight authentication and key agreement scheme for VANETs. In the proposed scheme, there are three types of mutual authentications: 1) between vehicles; 2) between vehicles and their respective cluster heads; and 3) between cluster heads and their respective roadside units. Apart from these authentications, the proposed scheme also maintains secret keys between roadside units for their secure communications. The rigorous formal and informal security analysis shows that the proposed scheme is capable to defend various malicious attacks. Moreover, the ns-2 simulation demonstrates the practicability of the proposed scheme in VANET environment.
A Theoretical Framework for Structured Prediction using Factor Graph Complexity ∗
(2016)

We present a general theoretical analysis of structured prediction. By introducing a new complexity measure that explicitly factors in the structure of the output space and the loss function, we are able to derive new data-dependent learning guarantees for a broad family of losses and for hypothesis sets with an arbitrary factor graph decomposition. To the best of our knowledge, these are both the most favorable and the most general guarantees for structured prediction (and multiclass classification) currently known. We also extend this theory by leveraging the principle of Voted Risk Minimization (VRM) and showing that learning is possible with complex factor graphs. We both present new learning bounds in this advanced setting as well as derive two new families of algorithms, Voted Conditional Random Field and Voted Structured Boosting, which can make use of very complex features and factor graphs without overfitting. Finally, we validate our theory through experiments on several datasets.
Theoretical perspectives on the relation between catastrophizing and pain.
(2001)

The tendency to "catastrophize" during painful stimulation contributes to more intense pain experience and increased emotional distress. Catastrophizing has been broadly conceived as an exaggerated negative "mental set" brought to bear during painful experiences. Although findings have been consistent in showing a relation between catastrophizing and pain, research in this area has proceeded in the relative absence of a guiding theoretical framework. This article reviews the literature on the relation between catastrophizing and pain and examines the relative strengths and limitations of different theoretical models that could be advanced to account for the pattern of available findings. The article evaluates the explanatory power of a schema activation model, an appraisal model, an attention model, and a communal coping model of pain perception. It is suggested that catastrophizing might best be viewed from the perspective of hierarchical levels of analysis, where social factors and social goals may play a role in the development and maintenance of catastrophizing, whereas appraisal-related processes may point to the mechanisms that link catastrophizing to pain experience. Directions for future research are suggested.
A realist review of mobile phone-based health interventions for non-communicable disease management in sub-Saharan Africa
(2017)

BACKGROUND
The prevalence of non-communicable diseases (NCDs) is increasing in sub-Saharan Africa. At the same time, the use of mobile phones is rising, expanding the opportunities for the implementation of mobile phone-based health (mHealth) interventions. This review aims to understand how, why, for whom, and in what circumstances mHealth interventions against NCDs improve treatment and care in sub-Saharan Africa.


METHODS
Four main databases (PubMed, Cochrane Library, Web of Science, and Google Scholar) and references of included articles were searched for studies reporting effects of mHealth interventions on patients with NCDs in sub-Saharan Africa. All studies published up until May 2015 were included in the review. Following a realist review approach, middle-range theories were identified and integrated into a Framework for Understanding the Contribution of mHealth Interventions to Improved Access to Care for patients with NCDs in sub-Saharan Africa. The main indicators of the framework consist of predisposing characteristics, needs, enabling resources, perceived usefulness, and perceived ease of use. Studies were analyzed in depth to populate the framework.


RESULTS
The search identified 6137 titles for screening, of which 20 were retained for the realist synthesis. The contribution of mHealth interventions to improved treatment and care is that they facilitate (remote) access to previously unavailable (specialized) services. Three contextual factors (predisposing characteristics, needs, and enabling resources) influence if patients and providers believe that mHealth interventions are useful and easy to use. Only if they believe mHealth to be useful and easy to use, will mHealth ultimately contribute to improved access to care. The analysis of included studies showed that the most important predisposing characteristics are a positive attitude and a common language of communication. The most relevant needs are a high burden of disease and a lack of capacity of first-contact providers. Essential enabling resources are the availability of a stable communications network, accessible maintenance services, and regulatory policies.


CONCLUSIONS
Policy makers and program managers should consider predisposing characteristics and needs of patients and providers as well as the necessary enabling resources prior to the introduction of an mHealth intervention. Researchers would benefit from placing greater attention on the context in which mHealth interventions are being implemented instead of focusing (too strongly) on the technical aspects of these interventions.
Visual attention measures for multi-screen TV
(2014)

We introduce a set of nine measures to characterize viewers' visual attention patterns for multi-screen TV. We apply our measures during an experiment involving nine screen layouts with two, three, and four TV screens, for which we report new findings on visual attention. For example, we found that viewers need an average discovery time up to 4.5 seconds to visually fixate four screens, and their perceptions of how long they watched each screen are substantially accurate, i.e., we report Pearson correlations up to .892 with measured eye tracking data. We hope our set of new measures (and the companion toolkit to compute them automatically) will benefit the community as a first step toward understanding visual attention for emerging multi-screen TV applications.
A first look at traffic on smartphones
(2010)

Using data from 43 users across two platforms, we present a detailed look at smartphone traffic. We find that browsing contributes over half of the traffic, while each of email, media, and maps contribute roughly 10%. We also find that the overhead of lower layer protocols is high because of small transfer sizes. For half of the transfers that use transport-level security, header bytes correspond to 40% of the total. We show that while packet loss is the main factor that limits the throughput of smartphone traffic, larger send buffers at Internet servers can improve the throughput of a quarter of the transfers. Finally, by studying the interaction between smartphone traffic and the radio power management policy, we find that the power consumption of the radio can be reduced by 35% with minimal impact on the performance of packet exchanges.